the performance of canadian-based versus us-based …

The Performance of Canadian-Based Versus US-Based Mutual Fund

Managers in the US Stock Market

by

Aidin Alaei

Bachelor of Business Administration and Economics, Simon Fraser University, 2009

and

Amir Moghadamnia

Bachelor of Electrical Engineering, Sharif University of Technology, 2009

PROJECT SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR

THE DEGREE OF

MASTER OF FINANCIAL RISK MANAGEMENT

In the Financial Risk Management Program

of the Faculty of

Business Administration

© Aidin Alaei and Amir Moghadamnia 2010

SIMON FRASER UNIVERSITY

Summer 2010

All rights reserved. However, in accordance with the Copyright Act of Canada, this work may be

reproduced, without authorization, under the conditions for Fair Dealing. Therefore, limited reproduction

of this work for the purposes of private study, research, criticism, review and news reporting is likely to be

in accordance with the law, particularly if cited appropriately.

ii

APPROVAL

Name: Aidin Alaei and Amir Moghadamnia

Degree: Master of Financial Risk Management

Title of Project: Comprehensive Study of the North American Mutual Funds’ Performance

Supervisory Committee:

______________________________________

Robert Grauer

Senior Supervisor

Endowed University Professor, Faculty of Business

Administration

______________________________________

Alexander Vedrashko

Second Reader

Assistant Professor, Faculty of Business Administration

Date Approved: ______________________________________

iii

ABSTRACT

This paper compares the performance of the Canadian-based mutual funds with

the U.S-based mutual funds that only invest in U.S equity markets. The time horizon

under study is from 1990 to 2009. Moreover, the time period was broke down in to two

sub-periods to capture the effect of bull and bear market on the relative performance of

the funds under study. The results in this paper are of practical importance to Canadian

investors who seek exposure to U.S equity markets through investing in mutual funds.

Financial theories suggest that the performance of the two must be similar since both are

exposed to the same market and are large enough to be well diversified. Our results

suggest that U.S based mutual funds have out-performed the Canadian-based mutual

funds in the total period of 1990 to 2009. Additionally the gap between their

performances increased significantly in the period of 2000 to 2009.

Keywords: Performance measurement, Sharpe ratio, Unconditional Jensen’s Alpha,

Conditional Jensen’s Alpha, Fama-French three factor model, Carhart four factor model,

Canadian mutual funds, U.S mutual funds, Ranking of funds

iv

ACKNOWLEDGEMENTS

This research project would not have been possible without the support of many

people. We wish to express our gratitude to our supervisor, Dr.Grauer who was

abundantly helpful and offered invaluable assistance, support and guidance. We would

also like to thank our families for their support; you have been the winds beneath our

wings.

Table of Contents

APPROVAL ............................................................................................................................ii

ABSTRACT ............................................................................................................................ iii

Acknowledgements ............................................................................................................. iv

Table of Contents ................................................................................................................. v

List of Tables ....................................................................................................................... vi

1. Introduction ..................................................................................................................... 1

2. Performance Measures .................................................................................................... 3

2.1 Sharpe Ratio .............................................................................................................. 3

2.2 Jenson’s alpha ........................................................................................................... 3

2.3 Conditional alpha ...................................................................................................... 3

2.4 Fama-French three-factor alpha ................................................................................ 4

2.5 Carhart alpha ............................................................................................................. 5

3. Data ................................................................................................................................. 5

4. Empirical Results ............................................................................................................. 6

4.1 Mean and Standard Deviation .................................................................................. 6

4.2 Sharpe Ratio .............................................................................................................. 6

4.3 Unconditional Jenson’s alpha ................................................................................... 7

4.4 Conditional Jenson’s alpha ....................................................................................... 8

4.5 Fama-French alpha ................................................................................................... 9

4.6 Carhart alpha .......................................................................................................... 11

5. Conclusion .................................................................................................................... 12

APPENDICES .................................................................................................................. 14

References ........................................................................................................................ 23

v

vi

List of Tables

Table 1. Mean, Standard Deviation and The Sharpe Ratio ............................................... 13

Table 2. Unconditional Jensen’s Alpha ............................................................................. 14

Table 3. Conditional CAPM ............................................................................................... 15

Table 4. Fama-French ........................................................................................................ 17

Table 5. Carhart ................................................................................................................. 19

1

1. Introduction

The performance of mutual funds and mutual fund managers has captured the attention of

the academic, investor and finance professional communities over the last half century. There are

different views on what is the most appropriate tool for measuring mutual funds’ performance.

Perhaps the most influential breakthrough is due to Sharpe (1966), the Sharpe ratio which is a

risk-adjusted measure of reward per unit of risk (standard deviation). Following the findings of

Sharpe, Jensen (1968) suggested measuring the performance of funds above and beyond the

return of the market portfolio, commonly known as Jensen’s alpha. Many other scholars have

contributed to further improve on Jensen’s original model by adding independent variables and

conditions, Fama-French (1996), Carhart (1997) and Ferson and Schadt (1996).

In this paper we used the Sharpe ratio, the unconditional Jenson’s alpha, Fama and

French’s three factor alpha (1996), Carhart’s four factor alpha (1997) and Ferson and Schadt’s

conditional alpha (1996) to conclude on funds’ performance ranking relative to each other. We

studied the monthly returns for nine categories of U.S open-ended mutual fund managers, an

equally weighted portfolio of these funds and a portfolio of the Canadian-based mutual funds that

are only exposed to the U.S equity market. In order to compare the alphas of Canadian based

funds with U.S based funds we took the difference between their returns and tested for abnormal

returns of the difference. This method allows us to comment on the significance of the difference

of funds performance. We considered the time period of 1990 to 2009 as the total period of our

study. In addition, we analyzed the periods of 1990 to 2000 and 2000 to 2009 as two individual

ten years sub-periods to investigate the effect of bull (1990 to 2000) and bear (2000 to 2009)

markets on the managers’ performance.

Our study reveals a number of interesting insights about North American mutual fund

performance. First, Canadian-based funds under-perform American-based funds in the twenty

year period under study; they have performed the worst in the bear market of 2000 to 2009.

Second, U.S manager based Value and Blend funds have the best performance in the total period

according to the consensus of four out of five models used for this study. Third, U.S manager

based Medium capitalization funds have the best performance when compared to others in the

total period. Additionally, U.S manager based Large capitalization funds have the best

performance in the bull market of 1990 to 2000 and Small capitalization funds out-perform others

in the bear market since 2000.

2

This paper proceeds ad follows: Part one is a brief introduction; Part two explains the

data structure of our study; Part three explains the different models we used for our analysis; Part

four contains the empirical results we obtained, and Part five concludes our paper.

3

2. Performance Measures

2.1 Sharpe Ratio

The Sharpe ratio is the single most used performance measure. It measures the percentage

excess return per unit of risk (Standard Deviation) taken. Logically a higher Sharpe ratio would

be preferred for any fund. The ratio is defined as

(1)

Where Rp is the portfolio return, Rf is the risk free rate of return and is the Standard Deviation

of the portfolio return.

2.2 Jenson’s alpha

The Jenson’s alpha (1968), is primarily used to measure the abnormal return of assets.

According to the CAPM the excess return of a security must plot on the security market line

(SML). Jenson’s alpha measures the distance between the security’s actual return and the SML.

risk in contrast to the Sharpe ratio, which uses the standard deviation of the return as the measure

of risk, this model uses beta as the measure of. The alpha is calculated by estimating the

following regression

(2)

Where Rpt is the monthly portfolio return of portfolio p, Rft is the risk free rate of return and Rmt is

the market portfolio return at time t. The estimated intercept is referred as the Jenson’s alpha that

measures the abnormal return of the portfolio. The estimated slope, p = cov(Rp , Rm)/ m2,

measures the sensitivity of the portfolio’s return to market’s return. In most academic literature

is referred to as the systemic or un-diversifiable risk of the portfolio.

2.3 Conditional alpha

Under the unconditional form of CAPM the use of any publicly available information

may lead to abnormal performance since the underlying assumption is that the investor holds

unconditional expectations. Assuming the semi-strong form of market efficiency hypothesis

holds, asset prices must reflect all the publicly available information, possessing such information

p f

p

E R Rsharpe

p

( )pt ft p p mt ft ptR R R R u

4

should not imply abnormal performance. Ferson and Schadt (1996) suggest that conditioning the

original CAPM to a vector of information factors, that in theory and practice are used to form

expectations for future performances, would eliminate the bias mentioned above and at the same

time, control for the time varying betas and market premium. For the purpose of our study, the

conditional beta is defined as

(3)

Where is the one month lagged dividend yield, is the one month lagged yield on a

90-days U.S treasury bill and is the one month lagged yield spread between 10-year and 2-

year U.S Treasury bill. By substituting equation (3) in equation (2) we estimate the coefficients

by considering the following regression,

(4)

Where is the conditional alpha, is the unconditional beta. The coefficients , and

capture the variations in beta caused by dividend yield, short-term interest and yield spread,

respectively. Please note that both and are the excess returns of portfolio p and market

portfolio, respectively.

2.4 Fama-French three-factor alpha

Fama-French (1992) found that there is no linear relationship between average returns

and betas thus rejected the CAPM. In their writings, specifically Fama-French (1996), they

present their three-factor model. They found that the excess return of a security is related to three

factors:

1. Excess rate of return of the market portfolio.

2. Return on a porfolio of Small size stocks minus the return on a portfolio of Large size

stocks(SMB, Small Minus Big).

3. Return on a porfolio of stocks with high book-to-market ratio minus the return on a

portfolio of stocks with low book-to-market ratio(HML, High Minus Low). The sensitivity

factors of this model are estimated by running the following regression

(5)

Where Rpt, Rft, Rmt and p = cov(Rp , Rm)/ m2 , SMB is the expected premium of Small size

stocks, HML is the expected premium of stocks with high book-to-market ratios. sp and hp are the

sensitivity measures of a security with respect to SMB and HML, respectively.

0 1 1 2 1 3 1p p p t p t p tb b Dy b TB b YS

1tDy 1tTB

1tYS

0 1 1 2 1 3 1pt cp p mt p t mt p t mt p t mt ptR b R b Dy R b TB R b YS R u

cp 0 pb 1 pb 2 pb

3 pb

ptR mtR

( )pt ft p p mt ft p p ptR R R R s SMB h HML u

5

2.5 Carhart alpha

In most finance literature persistence in mutual fund performance is well documented but

not explained. Carhart (1997) attempts to explain the short-term persistency in mutual fund

returns by adding a fourth factor to the Fama-French model. Carhart (1997) claims that the

mutual fund returns can be explained by a performance attribution model consisting of four

elementary strategies: high versus low beta stocks, Large versus Small market cap stocks, Value

versus Growth stocks and one year return momentum versus contrarian stocks. The model is

defined as

(6)

Where Rpt, Rft, Rmt ,SMB, HML, p = cov(Rp , Rm)/ m2 , sp, hp are the same as previously stated

and MOM is the monthly momentum factor which is the average return on the two portfolios with

prior high returns minus the average return on the two portfolios with prior low returns and mp is

the sensitivity factor of a security with respect to MOM.

3. Data

In this study we use monthly returns, net of MER, of Canadian-based and U.S open-

ended mutual funds, which solely invest in U.S equities, from October 1990 to May 2009. The

data used for our study come from several sources. The monthly funds’ returns come from

Morningstar. Morningstar categorizes the U.S mutual funds into nine different sub-categories

based on the funds’ capitalization size and their fundamental characteristic (i.e. Value, Growth

and Blend, please refer to exhibit 1). In total we looked at 568 U.S funds. For the purpose of

comparison, we created nine equally weighted portfolios for each of the nine categories. Further,

we considered one equally weighted portfolio containing the former nine portfolios as a proxy for

U.S mutual fund returns for the period under study. The universe of Canadian-based mutual funds

is much smaller than their U.S counterparts. There are thirty Canadian-based funds that had

available data for the period under study. Again, we constructed an equally weighted portfolio

containing the thirty funds as a proxy for Canadian-based mutual funds that only invest in U.S

equity.

The monthly returns for market portfolio, SMB, HML and MOM for the Fama-French

and Carhart models are from Kenneth R. French Data Library1. The one month lagged dividend

yield data was obtained from CRSP Value weighted market index provided by Dr.Grauer. The

1

http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html

( )pt ft p p mt ft p p p ptR R R R s SMB h HML m MOM u

6

one-month lagged 90 days T-bill yield and yield spread, between 10-years and 2-years yields,

were gathered from Federal Reserves Bank of St. Louis’s Economic Data (FRED)2.

4. Empirical Results

4.1 Mean and Standard Deviation

Considering the total period since 1990, US-based funds have had a higher Mean and

Standard Deviation than Canadian-based funds. As documented in Table 1 Panel A, Value and

Blend asset allocation strategies have had a higher Mean in Small and Medium cap fund while

Growth asset mixtures have had higher Mean in Large cap funds. As one would expect, Growth

funds have had a higher Standard Deviation than Value and Blend funds.

[Table 1 Here]

Comparing the two sub-periods, US funds have had a higher Mean and Standard

Deviation in both periods. In both periods, Growth funds and also Smaller cap funds have had

higher Standard Deviation than the rest.

In terms of Mean, the interesting point is that in the first period Growth stocks were

better than the Blend funds and the Value funds were the least successful. However, in the second

period, Value funds were better than the Blend funds while the Growth funds have been the worst

to invest in.

4.2 Sharpe Ratio

Considering the results obtained in Table 1, US mutual funds have outperformed their

Canadian-based counter parts in the past two decades. Also among the different US mutual funds

categories, we can see that Small and Medium cap funds have outperformed the Large cap funds

since 1990. Moreover, Blend and Value funds have higher Sharpe ratios relative to the Growth

funds.

Table 1 Panels B and C contain Sharpe ratios of all the funds under study in two sub-

periods, period one from 1990 to 2000 and period two from 2000 to 2009. Comparing the two

periods reveals an interesting insight. US funds demonstrate better performance than Canadian-

based in both decades. Also, we can see that the Sharpe ratio dropped for both US and Canadian-

based mutual funds going from the first period to second; however, the Canadian-based Sharpe

2

http://research.stlouisfed.org/fred2/

7

ratio fell much more than the US ones. Another interesting result is that in the first period the

funds with higher market caps were much more successful than the smaller caps and also Growth

funds did much better than Blend and Value funds. However, in the second period the Small-cap

funds were more successful than the Large-cap funds and also the Value funds have beaten the

Blend and Growth funds.

4.3 Unconditional Jenson’s alpha

As mentioned Jenson’s alpha is used to measure the performance of mutual funds above

and beyond the market. Table 2 Panel A contains regression results of on equation (2) for the

period of 1990 to 2009. According to Jenson’s alpha test the U.S mutual funds have been

outperforming the Canadian-based mutual funds by over 20 basis points on a monthly basis. An

interesting result is that the alpha measure for the Canadian-based fund is statistically less than

zero at 5% significance level. The alphas of all the nine different categories of U.S mutual funds

are not statistically different from zero. Therefore, unlike the findings of Fersonand and Schadt

(1996), all expect two (Medium and Large Growth) have positive alphas. Just as the theory

suggests, all the betas are positive and significantly different from zero. According to our study,

U.S funds have a higher beta than Canadian-based funds, although the difference is marginal. The

difference between the performance of the two is 21 bps and is statistically significant at 5% level

(t-stat = 2.31). In the nine U.S based sub-categories of funds, the Growth asset mixture strategy

has the highest beta whereas the Value strategy has the lowest market sensitivity factor. The latter

finding is consistent with theory, taking beta as a measure of riskiness of an asset, Growth stocks

have a higher risk than the Value stocks hence a portfolio containing them should have a higher

beta than a portfolio of Value stocks. Small capitalization portfolios have the highest beta

compared to Large and Medium cap portfolios mainly because of their higher exposure to Small

capitalization stocks. According to R-square figures, this model explains 77 to 98 percent of the

variation in the excess return of the portfolios under study.

[Table 2 Here]

When we break the period into two ten year periods the results get even more interesting.

As documented in Table 2 Panel B, all the eleven portfolios under study have underperformed

compared to the market portfolio in the first period. The gap between Canadian-based and U.S

funds narrows in that period but still results are in favor of U.S funds. The difference between the

performance of the two is 3 bps and is insignificant at 5% level (t-stat =0.25). As was the case in

the total twenty year period, the portfolio of Canadian-based funds has a statistically significant

8

negative alpha. The ranking and magnitude of the betas stays the same as previously discussed.

The goodness of the fit of the model stays in the range of 70% to 99%.

It is not until the second period that the results take a dramatic change. Canadian-based

funds take a hard beating from the U.S funds. During the period of 2000-2009 U.S funds beat the

market by an average of 27 basis points while Canadian-based funds underperform the market by

an average of 18 basis points on a monthly basis (See Table 2 Panel C). More astonishing is the

fact that both alphas are statistically significant at 5% significance level. The difference between

the performance of the two is 44 bps and is significant at 5% level (t-stat = 3.33). Four out of the

total of nine different categories of U.S funds demonstrate alphas that are statistically greater than

zero at 5% significance level. Funds that contain Large, Medium and Small cap Value stocks

performed considerably better than the other categories. The ranking, magnitude and significance

of the betas remain the same as previously discussed. According to the data obtained from

Kenneth R. French Data Library, the monthly average excess market return during the first and

second period were 1.22 and -0.25 percent, hence our study suggests that fund managers perform

worst in bull markets and better in bear market conditions. The superb performance of Small-cap

Value funds in the second period is largely due to the fact that market portfolio experienced a

bubble burst in the year 2000, as the tech bubble came to an end. By definition Small-cap Value

funds invest in Small capitalization stock with lower Growth rate such as manufacturing,

financials, utility and energy stocks, hence their exposure to tech firms were minimal which is

clearly reflected in their relative performance. This claim is further evident from Value funds’

lower betas relative to other funds.

4.4 Conditional Jenson’s alpha

Tables 3 contain our findings using conditional beta. In contrast to the findings of

Fersoand and Schadt (1996) our results do not suggest substantial and significant changes in

alphas. None of the negative alphas obtained from the unconditional model change sign nor did

their significance (and ranking) changed after adding lagged dividend yield, T-Bill yield and yield

spread as conditional variables. The conditional model suggests, once again, that the U.S funds

have outperformed Canadian-based funds in the period from 1990 to 2009. The difference

between the performance of the two is 23 bps and is significant at 5%level (t-stat = 2.56).

Another interesting result drawn from the conditional model is the significance of the positive

coefficients of dividend yields. Black and Scholes (1974) argues that in an efficiently operating

capital market in which firms were optimizing shareholders’ interest, there would be no

9

observable relationship between risk-adjusted returns and the dividend yields. Our finding

suggests that in fact the relation between lagged dividend yield and risk-adjusted return is

statistically greater than zero in the period under study. It is worth mentioning that Value funds

have the highest coefficients on dividend yields. One possible explanation for the later

observation could be that the investment strategy of Value funds favors high dividend yield

stocks hence their returns are more positively related to higher dividend yield stocks. The

significance and ranking of the market betas remained the same as suggested by the unconditional

model. Coefficients on lagged T-Bill yield and yield spread are statistically insignificant. The

adjusted R-squares increased by very little implying that the explanatory power of the model did

not changed substantially.

[Table 3 Here]

Looking at the results for the two ten year sub-periods we observe the same behaviors as

suggested by the unconditional model. Canadian-based funds have underperformed the U.S funds

in both periods but more substantially in the second period. The difference between the

performance of the two is 5 bps and statistically insignificant at 5% level (t-stat = 0.37) in the first

period while the difference increases to 43 bps and become statistically significant at 5% level in

the second period (t-stat = 3.15). In the period of 1990-2000 all the eleven alphas remain

negative. In the period of 2000 to 2009 the same dramatic changes are apparent. With six of the

eleven funds having statistically significant positive alphas, the conditional model re-affirms the

superior performance of U.S funds compared to both the market portfolio and the Canadian-based

funds. The magnitude, significance and ranking of the sensitivity factors remain unchanged from

the results obtained by considering data of the total period. The adjusted R-squares show little or

no improvement to the explanatory power of the model when compared to R-squares obtained

from the unconditional model.

4.5 Fama-French alpha

Table 4 contains the regression results of equation (5). Considering the whole twenty year

period, the Fama-French model produces different results compared to the unconditional CAPM

model. In contrast to CAPM outputs, alphas for Growth funds are positive, all the other alphas are

negative and Value funds have the lowest alphas. Considering Table 4 Panel A, it is apparent that

the U.S funds have outperformed the Canadian-based funds. The difference between the

performance of the two is 13 bps and statistically significant at 5% level (t-stat = 2.02). The

Fama-French gives us the same ranking, significance and almost same magnitude of betas when

10

compared to the unconditional CAPM. The interesting results are from the coefficients of the

SMB and the HML. Only two of the eleven coefficients on the SMB factors are statistically not

different from zero, suggesting that the SMB factor is an adequate explanatory variable for

variations in excess returns of funds. The portfolios rank in terms of this factor sensitivity from

highest to lowest as: Small-cap, Medium-cap and Large-cap which is consistent with the findings

of the Fama-French (1996). It is worth noting that the portfolio consisting of the Canadian-based

funds not only has a lower SMB coefficient but it is also negative, suggesting that the Canadian-

based funds under study are exposed to the Large-cap stocks more than the Small-caps; whereas

the portfolio of the U.S funds has a high, positive SMB coefficient which could be a reason for

their superior performance compared to the Canadian-based funds. The sensitivity factors of

HML are all significant except for the Small-cap Growth and the Canadian-based portfolios,

implying that the HML factors do help us explain the variations in funds’ excess returns. Growth

funds have negative factor loadings, which is reasonable since Growth funds have more exposure

to stocks with low book-to-market ratios. The Canadian-based funds seem to be well balanced

between high and low book-to-market stocks since they have an insignificant and very Small

HML coefficient. Over this period, our study suggests higher positive sensitivity of the U.S funds

to the market portfolio, the SMB and the HML factors contributed to their superior performance

compared to the Canadian-based funds.

[Table 4 Here]

Returning to the two ten year sub-periods, in the first period, from 1990 to 2000, it is

evident from the alpha figures that all the funds except for Growth funds have underperformed

with respect to the market portfolio. In this period the Value funds did worse than other

categories since they have statistically significant negative alphas. The Canadian-based funds

show poorer performance compared to the U.S funds and the gap is much bigger than previously

suggested by the unconditional CAPM. The difference between the performance of the two is \5

bps and is statistically insignificant at 5%level (t-stat = 0.83). Betas of all funds in this period are

statistically significant and they rank from highest to lowest as: Growth, Blend and Value. The

coefficients on the SMB factor are all significant with the exception of the Large-cap Value fund

and the portfolio of Canadian-based funds. As was the case in the total period, Small cap funds

have the highest loading and Large cap funds have the lowest. The coefficients on the HML

factors in this period are all statistically significant except for the portfolio of Canadian-based

funds (the ranking and magnitude of the coefficients remain the same as previously mentioned).

The adjusted R-squares suggest that the Fama-French three-factor model fits the data for this

period almost perfectly (range from 93% to 99%, see Table 4 Panel B).

11

Table 4 Panel C contains the regression outputs for the period of 2000 to 2009.

Considering the alphas in this period, all the alphas are statistically not different from zero expect

for the portfolio of the Canadian-based funds which has a negative alpha. The difference between

the performance of the two is 26 bps and is significant at 5% level (t-stat =2.40) . All the betas in

this period are significant and positive and their ranking and magnitude remains the same as the

previous period. The coefficients on the SMB factors are all statistically significant except for

three funds (Large-cap Blend and Value, and Medium-cap Growth), with the same ranking as

before. The coefficients on the HML are statistically significant at 5% significance level with the

exception of Medium and Small cap Growth, and the portfolio of Canadian-based funds.

4.6 Carhart alpha

Tables 5 contains the statistical regression results of equation (6). During the total period,

from 1990 to 2009, the results are not significantly different from the results we got by using the

Fama-French (see Table 5 Panel A). In this period, alphas remain insignificant with the exception

of the portfolio of Canadian-based funds which has statistically less than zero alpha. The

difference between the performance of the Canadian based funds and the U.S based funds is 10

bps and is significant at 5% level (t-stat = 1.98). The betas of all the nine different categories of

funds remain very close to the market sensitivity coefficients suggested by the Fama-French

model; they remain positive and statistically significant at significant at 5% significance level.

The coefficients on the SMB for all the portfolios under study are positive and significant except

for two, Large-cap Growth and Canadian-based, while Large-cap Value coefficients are

insignificant. The coefficients on the SMB for the Canadian-based portfolio and the US portfolio

of funds are exactly the same as suggested by the Fama-French model mentioned previously. The

coefficients on the HML factors are all positive except for the Large, Medium and Small

capitalization Growth funds. The portfolio of Canadian-based funds has an insignificant HML

loading as was the case under the Fama-French model. The coefficients on momentum factor

(MOM) are all significant with the exception of Small-cap Blend and Value, and the portfolio of

the U.S and the Canadian-based funds. The MOM coefficients suggest that there is a significantly

positive relation between momentum and the excess returns of Growth funds, the reverse holds

for the Value funds. It is worth mentioning that the U.S and Canadian-based funds are not

sensitive to short term momentum. The adjusted R-Squares have improved significantly (lowest

figure is 95%) with the addition of the fourth factor.

12

[Table 5 Here]

Considering the regression results for the period between 1990 and 2000 the alphas for all

the eleven portfolios under study are negative and not significant except for the portfolio of

Canadian-based funds which has a statistically significant negative alpha. The difference between

the performance of the Canadian based funds and the U.S based funds is 9 bps and is statistically

insignificant at 5% level (t-stat = 1.37). The market sensitivity loadings of every other fund

remains positive and statistically significant at 5% significance level; their ranking and magnitude

remains the same as the total period, expect during this period the portfolio of Canadian-based

funds has a higher beta than the U.S portfolio. The coefficients on the SMB factor are significant

and positive with Growth funds having the highest loadings and the exception of Large-cap Value

and the portfolio of Canadian-based funds which have negative coefficients. The coefficients on

the HML behave in the same manner as the first period; they are all significant except for the

Canadian-based portfolio, and are positive except for the Growth funds. The coefficients on the

momentum factor remain significant except for the U.S and the Canadian-based portfolios while

the Growth funds remain the only funds with a positive MOM loading. The adjusted R-Square

measures indicate a very good fitted model to data in this period.

In the period of 2000-2009 the alphas are, once again, statistically not different from zero

except for the portfolio of Canadian-based funds. As other models suggest, during this time

period the gap between the portfolio of Canadian-based and American funds increase the most.

The difference between the performance of the Canadian based funds and the U.S based funds is

26 bps and is significant at 5% level (t-stat = 2.50). The market sensitivity measures, betas,

remain positive and significant. As other models suggest, in this period, Small capitalization and

Growth funds have the highest betas. The coefficients on the SMB are positive in this period,

except for the Large-cap Growth, the Blend and the Canadian-based funds. The coefficients on

the HML factor remain significant for all eleven funds under study with the exception of the

portfolio of the Canadian-based funds. The HML loadings are significantly less than zero for the

Growth funds. The coefficients on the momentum factor are negative except for the Growth funds

which have positive sensitivities to momentum. Eight of the eleven funds under study have

coefficients on the MOM that are statistically different from zero at 5% significance level.

5. Conclusion

In conclusion, our findings can be summarized into three categories. First, we have found

that the portfolio of Canadian-based open-ended mutual funds has lower performance measures

13

compared to the U.S funds in the twenty year period. Although the gap between them is marginal

during the first period but it widens significantly over the second period. According to

Morningstar’s website, on average, the Canadian-based funds have a higher MER relative to the

US funds. Hence we suspect that the difference between the performance of the US and the

Canadian-based funds is mainly due to different management expense ratios.

Second, in view of our empirical findings, Large funds have the worst performance over

the total period. Moreover, Medium funds achieve superior returns according to the Carhart,

Sharpe and Fama-French models. However, both Unconditional and Conditional CAPM suggest

Small capitalization funds are the better performers. Considering each of the two ten year sub-

periods, we observe that the Large capitalization funds have performed the best compared to the

others in the first sub-period while Small-cap funds showed the worst performance; however, the

Small-cap funds have the best performance in the second sub-period.

Third, regarding the different investment strategies our findings suggest that Blend funds

have had the worst performance in the total period since 1990 additionally, the Value funds

performed better according to the Unconditional Jensen’s alpha, Conditional CAPM, Sharpe and

Carhart models. However, the Fama-French three-factor model suggests that Growth funds

performed the best during this period. Considering each of the two ten year sub-periods, our

findings show that during the first period, Blend funds performed better compared to other

categories according to all the models except the Fama-French, which suggests Growth funds are

the best performers. In the second period, the Sharpe ratio, the Unconditional Jensen’s alpha and

the conditional CAPM conclude that the Value funds have the best performance while the Carhart

and the Fama-French suggest that the Growth funds are the better performers.

14

APPENDICES

Exhibit 1

Large Value: Large-Value funds focus on big companies that are less expensive or growing

more slowly than other large-cap stocks.

Large Blend: Large-Blend funds have portfolios that are fairly representative of the overall stock

market in size, Growth rates, and price. They tend to invest across the spectrum of U.S. industries

and owing to their broad exposure; the funds returns are often similar to those of the S&P 500

Index.

Large Growth: Large-Growth funds invest in big companies that are projected to grow faster

than other large-cap stocks. Most of these funds focus on companies in rapidly expanding

industries.

Mid-Cap Value: Some mid-cap Value funds focus on medium-size companies while others land

here because they own a mix of small-, mid-, and large-cap stocks. All look for stocks that are

less expensive or growing more slowly than the market.

Mid-Cap Blend: The typical mid-cap Blend fund invests in stocks of various sizes and mixed

characteristics, giving it a middle-of-the-road profile. Most shy away from high-priced Growth

stocks, but are not so price-conscious that they land in Value territory.

Mid-Cap Growth: Some mid-cap Growth funds invest in stocks of all sizes, thus leading to a

mid-cap profile, but others focus on midsize companies. Mid-cap Growth funds target firms that

are projected to grow faster than other mid-cap stocks, therefore commanding relatively higher

prices. Many of these stocks are found in the volatile technology, health-care, and services

sectors.

Small Value: Small-Value funds invest in small-caps with valuations and Growth rates below

other small-cap peers. They tend to invest in manufacturing, financial, and energy sectors.

Small Blend: Small-Blend funds favor firms at the smaller end of the market-capitalization

range, and are flexible in the types of small caps they buy. Some aim to own an array of Value

and Growth stocks while others employ a discipline that leads to holdings with valuations and

Growth rates close to the small-cap averages.

Small Growth: Small-Growth funds focus on faster-growing companies whose shares are at the

lower end of the market-capitalization range. These funds tend to favor companies in up-and-

coming industries or young firms in their early Growth stages. As a result, the category tends to

move in sync with the market for initial public offerings. Many of these funds invest in the

technology, health-care, and services sectors. Because these businesses are fast growing and often

richly valued, their stocks tend to be volatile.

15

Table 1.

Mean, Standard Deviation and Sharpe Ratio

The mean and the standard deviation of each fund is calculated based on excess return of each

fund. The Sharpe ratio indicates the excess return per unit of risk and is defined as

p f

p

E R RSharpe ,

Where Rp is the portfolio return, Rf is the risk free rate of return and is the standard deviation

of the portfolio return.

p

U.S Managers U.S

Managers

Total

Canadian

Managers

Total

Large Cap Medium Cap Small Cap

Growth Blend Value Growth Blend Value Growth Blend Value

Panel A: 1990-2009 Sharpe Ratio 0.10 0.11 0.11 0.10 0.13 0.14 0.10 0.14 0.13 0.12 0.08

Mean 0.47 0.44 0.43 0.56 0.58 0.61 0.60 0.66 0.63 0.55 0.33

Standard Deviation 4.69 4.02 3.81 5.58 4.46 4.23 6.04 4.80 4.74 4.48 4.24

Panel B: 1990-2000

Sharpe Ratio 0.33 0.34 0.30 0.28 0.29 0.28 0.27 0.26 0.23 0.30 0.30

Mean 1.36 1.15 0.94 1.34 1.05 0.93 1.37 1.03 0.94 1.13 1.10


Panel C: 2000-2009

Sharpe Ratio -0.08 -0.06 -0.01 -0.03 0.02 0.06 -0.02 0.06 0.06 0.00 -0.09

Mean -0.41 -0.27 -0.06 -0.22 0.11 0.29 -0.17 0.30 0.31 -0.01 -0.44


16

Table 2.

Unconditional Jensen’s Alpha

Jenson’s alpha (1968) is defined as ,where Rpt is the

monthly portfolio return of portfolio p, Rft is the risk free rate of return and Rmt is the market

portfolio return at time t. The estimated intercept is referred as the Jenson’s alpha that measures

the abnormal return of the portfolio. The estimated slope, p = cov(Rp , Rm)/ m2, measures the

sensitivity of the portfolio’s return to market’s return.

( )pt ft p p mt ft ptR R R R u

U.S Managers U.S

Managers

Total

Canadian

Managers

Total



Panel A: 1990-2009

t-Stat)

-0.04

(-0.58)

0.00

(-0.02)

0.05

(0.47)

-0.01

(-0.07)

0.11

(1.12)

0.19

(1.47)

0.00

(0.00)

0.20

(1.28)

0.17

(1.09)

0.07

(0.93)

-0.14

(-3.09)

(t-Stat)

1.04

(70.41)

0.90

(90.75)

0.79

(33.68)

1.16

(35.17)

0.95

(41.57)

0.85

(28.84)

1.22

(29.91)

0.95

(27.57)

0.94

(26.72)

0.98

(54.14)

0.95

(95.20)

R2 0.96 0.97 0.84 0.85 0.89 0.79 0.80 0.77 0.76 0.93 0.98

Panel B: 1990-2000

(t-Stat)

-0.02

(-0.18)

-0.02

(-0.54)

-0.07

(-0.66)

-0.17

(-0.95)

-0.12

(-0.86)

-0.10

(-0.64)

-0.17

(-0.66)

-0.11

(-0.49)

-0.23

(-1.03)

-0.11

(-0.95)

-0.14

(-2.74)

(t-Stat)

1.08

(44.81)

0.92

(88.41)

0.79

(29.13)

1.19

(25.16)

0.92

(25.31)

0.81

(20.57)

1.21

(18.31)

0.89

(15.55)

0.92

(16.10)

0.97

(31.83)

0.98

(72.13)

R2 0.95 0.99 0.89 0.85 0.85 0.80 0.75 0.69 0.70 0.90 0.98

Panel C: 2000-2009

(t-Stat)

-0.12

(-1.34)

-0.02

(-0.28)

0.16

(0.88)

0.11

(0.46)

0.38

(2.61)

0.54

(2.55)

0.18

(0.68)

0.59

(2.74)

0.58

(2.65)

0.27

(2.40)

-0.18

(-2.51)

(t-Stat)

1.01

(53.43)

0.88

(56.08)

0.79

(21.62)

1.15

(24.25)

0.98

(32.92)

0.89

(20.86)

1.24

(22.84)

1.01

(23.23)

0.97

(21.60)

0.99

(43.96)

0.93

(64.53)

R2 0.96 0.97 0.81 0.84 0.91 0.80 0.82 0.83 0.81 0.95 0.97

17

Table 3.

Conditional Jensen’s Alpha

For the purpose of our study, the conditional beta is defined as

Where is the one month lagged dividend yield, is the one month lagged yield on a

90-days U.S treasury bill and is the one month lagged yield spread between 10-year and 2-

year U.S Treasury bill. By substituting the above equation in to the unconditional CAPM we have

Where is the conditional alpha, is the unconditional beta. The coefficients , and

capture the variations in beta caused by dividend yield, short-term interest and yield spread,

respectively. Please note that both and are the excess returns of portfolio p and market

portfolio, respectively.

0 1 1 2 1 3 1p p p t p t p tb b Dy b TB b YS

1tDy 1tTB

1tYS

0 1 1 2 1 3 1pt cp p mt p t mt p t mt p t mt ptR b R b Dy R b TB R b YS R u

cp 0 pb 1 pb 2 pb

3 pb

ptR mtR

U.S Managers U.S

Managers

Total

Canadian

Managers

Total



Panel A: 1990-2009

(t-Stat)

-0.08

(-1.26)

0.01

(0.14)

0.10

(0.99)

-0.06

(-0.40)

0.16

(1.70)

0.28

(2.32)

-0.04

(-0.21)

0.26

(1.76)

0.22

(1.48)

0.09

(1.20)

-0.14

(-3.21)

(t-Stat)

0.83

(10.05)

0.75

(13.50)

0.61

(4.84)

1.15

(6.01)

0.98

(7.74)

0.88

(5.59)

1.16

(4.82)

0.92

(4.74)

0.84

(4.21)

0.90

(8.65)

0.79

(13.63)

(t-Stat)

-4.51

(-1.99)

3.50

(2.27)

9.25

(2.63)

-8.28

(-1.56)

8.23

(2.34)

12.35

(2.84)

-5.38

(-0.81)

16.50

(3.06)

15.39

(2.80)

5.23

(1.81)

2.18

(1.36)

(t-Stat)

0.06

(4.43)

0.01

(0.84)

-0.02

(-1.11)

0.04

(1.44)

-0.05

(-2.43)

-0.07

(-2.96)

0.04

(1.01)

-0.06

(-2.06)

-0.05

(-1.52)

-0.01

(-0.73)

0.02

(1.94)

(t-Stat)

0.10

(2.95)

0.04

(1.89)

0.05

(0.99)

0.03

(0.41)

-0.04

(-0.71)

-0.03

(-0.47)

0.04

(0.39)

-0.08

(-1.06)

-0.05

(-0.61)

0.01

(0.16)

0.05

(2.14)

R2 0.96 0.98 0.86 0.86 0.90 0.83 0.80 0.80 0.78 0.93 0.98

0 pb

1 pb

2 pb

3 pb

18

Table 3. Continue

U.S Managers U.S

Managers

Total

Canadian

Managers

Total Large Cap Medium Cap Small Cap


Panel B: 1990-2000

(t-Stat)

-0.05

(-0.51)

-0.02

(-0.39)

-0.03

(-0.35)

-0.21

(-1.12)

-0.09

(-0.62)

-0.04

(-0.28)

-0.19

(-0.72)

-0.08

(-0.36)

-0.19

(-0.86)

-0.10

(-0.84)

-0.15

(-2.78)

(t-Stat)

0.67

(3.08)

1.00

(11.14)

1.13

(4.91)

0.68

(1.58)

1.25

(3.81)

1.38

(4.06)

0.82

(1.35)

0.92

(1.79)

1.27

(2.46)

1.01

(3.69)

0.93

(7.60)

(t-Stat)

-12.96

(-1.44)

9.89

(2.65)

37.88

(3.95)

-20.68

(-1.15)

29.13

(2.14)

52.55

(3.72)

1.13

(0.04)

44.43

(2.09)

43.32

(2.03)

20.52

(1.80)

3.20

(0.63)

(t-Stat)

0.11

(1.83)

-0.05

(-1.91)

-0.18

(-2.82)

0.16

(1.31)

-0.15

(-1.61)

-0.26

(-2.78)

0.07

(0.40)

-0.14

(-0.95)

-0.20

(-1.40)

-0.07

(-0.93)

0.00

(-0.12)

(t-Stat)

0.20

(2.02)

-0.06

(-1.40)

-0.32

(-2.97)

0.23

(1.13)

-0.29

(-1.86)

-0.51

(-3.18)

0.05

(0.19)

-0.37

(-1.56)

-0.35

(-1.44)

-0.16

(-1.22)

0.01

(0.20)

R2 0.95 0.99 0.90 0.86 0.86 0.82 0.76 0.71 0.72 0.91 0.98

Panel C: 2000-2009

(t-Stat)

-0.14

(-1.56)

-0.05

(-0.73)

0.09

(0.55)

0.11

(0.49)

0.36

(2.61)

0.45

(2.44)

0.20

(0.75)

0.58

(2.79)

0.57

(2.67)

0.24

(2.17)

-0.19

(-2.75)

(t-Stat)

1.18

(3.89)

1.14

(4.65)

1.32

(2.43)

1.23

(1.56)

1.17

(2.55)

1.74

(2.81)

1.09

(1.19)

1.16

(1.66)

1.09

(1.50)

1.24

(3.31)

1.03

(4.33)

(t-Stat)

-8.69

(-1.83)

-3.45

(-0.90)

-5.18

(-0.61)

-7.32

(-0.59)

2.97

(0.41)

-4.99

(-0.51)

-2.96

(-0.21)

10.32

(0.94)

9.79

(0.86)

-1.06

(-0.18)

-2.25

(-0.60)

(t-Stat)

0.00

(0.09)

-0.06

(-1.62)

-0.14

(-1.71)

0.04

(0.35)

-0.08

(-1.15)

-0.21

(-2.24)

0.07

(0.50)

-0.09

(-0.86)

-0.09

(-0.78)

-0.06

(-1.09)

-0.03

(-0.75)

(t-Stat)

0.00

(0.00)

-0.03

(-0.52)

-0.07

(-0.45)

-0.02

(-0.09)

-0.05

(-0.38)

-0.18

(-1.06)

0.03

(0.13)

-0.10

(-0.55)

-0.09

(-0.45)

-0.06

(-0.56)

0.00

(0.02)

R2 0.97 0.97 0.86 0.86 0.93 0.86 0.83 0.85 0.83 0.95 0.98

0 pb

1 pb

2 pb

3 pb

0 pb

1 pb

2 pb

3 pb

19

Table 4.

Fama-French

The sensitivity factors of this model are estimated by running the following regression

, where Rpt, Rft, Rmt and p = cov(Rp ,

Rm)/ m2 , SMB is the expected premium of small size stocks, HML is the expected premium of

stocks with high book-to-market ratios. sp and hp are the sensitivity measures of a security with

respect to SMB and HML, respectively.

( )pt ft p p mt ft p p ptR R R R s SMB h HML u

U.S Managers U.S

Managers

Total

Canadian

Managers

Total



Panel A: 1990-2009

(t-Stat)

0.05

(0.77)

-0.04

(-1.12)

-0.12

(-1.45)

0.07

(0.47)

-0.03

(-0.35)

-0.05

(-0.53)

0.05

(0.31)

-0.02

(-0.19)

-0.07

(-0.81)

-0.03

(-0.52)

-0.14

(-3.12)

(t-Stat)

1.01

(73.37)

0.92

(101.41)

0.86

(44.15)

1.11

(34.26)

0.97

(56.26)

0.92

(43.07)

1.15

(31.89)

0.97

(46.81)

0.97

(47.16)

0.99

(69.32)

0.95

(91.18)

s

(t-Stat)

-0.03

(-1.53)

-0.04

(-3.83)

0.02

(1.01)

0.17

(4.17)

0.27

(12.46)

0.25

(9.32)

0.40

(8.80)

0.52

(19.83)

0.52

(19.76)

0.24

(13.44)

-0.05

(-3.92)

h

(t-Stat)

-0.15

(-7.92)

0.07

(5.79)

0.31

(11.38)

-0.12

(-2.76)

0.27

(11.30)

0.45

(15.26)

-0.06

(-1.14)

0.42

(14.62)

0.47

(16.50)

0.19

(9.81)

0.01

(1.04)

R2 0.97 0.98 0.90 0.87 0.94 0.90 0.86 0.93 0.93 0.96 0.98

Panel B: 1990-2000

(t-Stat)

0.09

(1.35)

-0.06

(-1.90)

-0.22

(-3.14)

0.02

(0.15)

-0.14

(-1.78)

-0.23

(-2.49)

0.06

(0.55)

-0.13

(-1.67)

-0.28

(-2.78)

-0.07

(-1.23)

-0.16

(-2.78)

(t-Stat)

0.99

(47.91)

0.96

(99.99)

0.92

(44.32)

1.03

(34.61)

0.94

(40.45)

0.93

(33.54)

1.02

(31.38)

0.92

(39.83)

0.97

(32.81)

0.96

(62.54)

0.99

(61.63)

s

(t-Stat)

0.09

(4.09)

-0.05

(-4.82)

0.01

(0.64)

0.42

(12.59)

0.42

(15.91)

0.35

(11.19)

0.71

(19.33)

0.74

(28.44)

0.70

(20.94)

0.37

(21.03)

-0.01

(-0.29)

h

(t-Stat)

-0.21

(-7.46)

0.07

(5.22)

0.34

(11.80)

-0.27

(-6.50)

0.19

(5.89)

0.42

(11.00)

-0.26

(-5.74)

0.31

(9.69)

0.35

(8.74)

0.09

(4.20)

0.02

(0.77)

20

Table 4. Continue

U.S Managers

U.S

Managers

Total

Canadian

Managers

Total Large Cap Medium Cap Small Cap Growth Blend Value Growth Blend Value Growth Blend Value

R2 0.97 0.99 0.95 0.96 0.96 0.93 0.96 0.96 0.94 0.98 0.98

Panel C: 2000-2009

(t-Stat)

0.00

(0.00)

-0.10

(-1.40)

-0.12

(-0.79)

0.19

(0.79)

0.11

(0.95)

0.11

(0.74)

0.17

(0.65)

0.15

(1.12)

0.09

(0.73)

0.07

(0.77)

-0.20

(-3.04)

(t-Stat)

1.00

(58.86)

0.90

(63.84)

0.82

(26.90)

1.13

(23.41)

0.98

(43.51)

0.92

(29.33)

1.19

(22.66)

1.00

(36.54)

0.96

(39.41)

1.00

(52.18)

0.92

(64.35)

s

(t-Stat)

-0.09

(-3.94)

-0.03

(-1.74)

0.04

(0.93)

0.03

(0.50)

0.19

(6.53)

0.20

(4.84)

0.23

(3.35)

0.40

(11.31)

0.42

(13.19)

0.16

(6.88)

-0.07

(-3.88)

h

(t-Stat)

-0.13

(-5.43)

0.09

(4.62)

0.31

(7.27)

-0.10

(-1.41)

0.29

(9.16)

0.46

(10.46)

-0.02

(-0.24)

0.45

(11.62)

0.51

(14.98)

0.21

(8.52)

0.03

(1.58)

R2 0.97 0.97 0.87 0.85 0.95 0.90 0.84 0.94 0.95 0.97 0.98

21

Table 5.

Carhart

The model is defined as

Where Rpt, Rft, Rmt ,SMB, HML, p = cov(Rp , Rm)/ m2 , sp, hp are the same as previously stated

and MOM is the monthly momentum factor which is the average return on the two portfolios with

prior high returns minus the average return on the two portfolios with prior low returns and mp is

the sensitivity factor of a security with respect to MOM.

( )pt ft p p mt ft p p p ptR R R R s SMB h HML m MOM u

Open Ended U.S Mutual Funds U.S

Managers

Total

Canadian

Managers

Total



Panel A: 1990-2009

(t-Stat)

-0.01

(-0.19)

-0.02

(-0.45)

-0.04

(-0.47)

-0.08

(-0.61)

0.01

(0.08)

0.03

(0.40)

-0.09

(-0.63)

-0.03

(-0.29)

-0.06

(-0.63)

-0.03

(-0.52)

-0.14

(-3.12)

(t-Stat)

1.03

(77.33)

0.91

(99.29)

0.82

(44.12)

1.17

(37.83)

0.96

(53.75)

0.88

(42.38)

1.21

(34.29)

0.98

(44.91)

0.96

(44.83)

0.99

(69.32)

0.95

(91.18)

s

(t-Stat)

-0.01

(-0.92)

-0.05

(-4.43)

0.01

(0.32)

0.20

(5.34)

0.27

(12.21)

0.23

(9.20)

0.43

(10.03)

0.53

(19.73)

0.51

(19.50)

0.24

(13.44)

-0.05

(-3.92)

h

(t-Stat)

-0.14

(-7.56)

0.07

(5.33)

0.28

(11.31)

-0.08

(-2.01)

0.26

(10.94)

0.43

(15.31)

-0.02

(-0.37)

0.43

(14.54)

0.47

(16.18)

0.19

(9.81)

0.01

(1.04)

m

(t-Stat)

0.06

(6.01)

-0.03

(-4.13)

-0.09

(-6.49)

0.16

(6.69)

-0.04

(-2.55)

-0.09

(-5.68)

0.16

(5.71)

0.01

(0.64)

-0.02

(-0.98)

0.01

(1.23)

-0.01

(-1.83)

R2 0.97 0.98 0.92 0.89 0.94 0.91 0.88 0.93 0.93 0.96 0.98

Panel B: 1990-2000

(t-Stat)

-0.02

(-0.30)

-0.02

(-0.72)

-0.06

(-1.06)

-0.13

(-1.35)

-0.07

(-0.87)

-0.05

(-0.63)

-0.06

(-0.54)

-0.02

(-0.30)

-0.17

(-1.71)

-0.07

(-1.23)

-0.16

(-2.78)

(t-Stat)

0.99

(54)

0.96

(106)

0.92

(59)

1.04

(38)

0.94

(41)

0.92

(40)

1.03

(33)

0.91

(43)

0.97

(34)

0.96

(63)

0.99

(62)

s

(t-Stat)

0.12

(5.59)

-0.06

(-5.73)

-0.02

(-0.94)

0.45

(14.48)

0.40

(15.58)

0.31

(11.93)

0.73

(20.57)

0.72

(29.51)

0.68

(20.88)

0.37

(21.03)

-0.01

(-0.29)

22

Table 5. Continue

U.S Managers U.S

Managers

Total

Canadian

Managers

Total Large Cap Medium Cap Small Cap Growth Blend Value Growth Blend Value Growth Blend Value

h

(t-Stat)

-0.17

(-6.46)

0.05

(4.21)

0.28

(12.52)

-0.21

(-5.44)

0.16

(5.00)

0.35

(10.67)

-0.21

(-4.77)

0.27

(8.78)

0.31

(7.78)

0.09

(4.20)

0.02

(0.77)

m

(t-Stat)

0.10

(5.57)

-0.04

(-3.77)

-0.15

(-9.45)

0.13

(4.79)

-0.06

(-2.76)

-0.17

(-7.07)

0.11

(3.44)

-0.10

(-4.52)

-0.10

(-3.34)

-0.03

(-1.85)

0.01

(0.35)

R2 0.98 0.99 0.97 0.97 0.96 0.95 0.96 0.97 0.95 0.98 0.98

Panel C: 2000-2009

(t-Stat)

0.00

(-0.01)

-0.10

(-1.50)

-0.12

(-0.85)

0.19

(0.88)

0.11

(0.97)

0.12

(0.79)

0.17

(0.71)

0.15

(1.13)

0.09

(0.73)

0.07

(0.77)

-0.20

(-3.04)

(t-Stat)

1.04

(58.97)

0.87

(60.32)

0.76

(24.64)

1.25

(26.32)

0.96

(39.06)

0.86

(26.55)

1.31

(24.94)

1.02

(34.19)

0.95

(35.29)

1.00

(52.18)

0.92

(64.35)

SMB

(t-Stat)

-0.08

(-4.02)

-0.04

(-2.08)

0.03

(0.79)

0.05

(0.83)

0.19

(6.52)

0.19

(4.95)

0.25

(3.97)

0.41

(11.50)

0.42

(13.11)

0.16

(6.88)

-0.07

(-3.88)

HML

(t-Stat)

-0.13

(-5.78)

0.09

(4.92)

0.31

(7.92)

-0.09

(-1.53)

0.29

(9.27)

0.46

(11.08)

-0.01

(-0.20)

0.45

(11.76)

0.51

(14.93)

0.21

(8.52)

0.03

(1.58)

MOM

(t-Stat)

0.05

(4.20)

-0.04

(-4.26)

-0.10

(-4.79)

0.19

(5.59)

-0.04

(-2.05)

-0.09

(-3.89)

0.19

(5.13)

0.04

(1.82)

-0.01

(-0.63)

0.02

(1.50)

-0.03

(-3.17)

R2 0.98 0.98 0.90 0.88 0.95 0.91 0.88 0.94 0.95 0.97 0.98

23

References

Black, F., and Scholes, M., 1974. The Effects Of Dividend Yield And Dividend Policy

On Common Stock Prices And Returns. Journal of Financial Economics 1, 1-22.

Fama, E. F., and French, K. R. (1996). Multifactor Explanations of Asset Pricing

Anomalies. Journal of Finance , 55-84.

Ferson, W. E., and Schadt, R. W. (1996). Measuring Fund Strategy and Performance in

Changing Economic Conditions. Journal of Finance , 425-459.

Jensen, M. C. (1968). The Performance of Mutual Funds in the Period 1945-1964.

Journal of Finance , 389-416.

Carhart, M. M. (1997). On Persistence in Mutual Fund Performance. Journal of Finance ,

57-81.

Sharpe, W. F. (1966). Mutual Fund Performance. Journal of Business 39 , 119-138

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